Understanding the mechanism of intelligence in human beings and animals is
one of the most important approaches to developing intelligent robot
systems. Since the mechanisms of such real-life intelligent systems are so
complex, such as the physical interactions between agents and their
environment and the social interactions between agents, comprehension and
knowledge in many peripheral fields such as cognitive science,
developmental psychology, brain science, evolutionary biology, and
robotics. Discussions from an interdisciplinary aspect are very important
for implementing this approach, but such collaborative research is
time-consuming and labor-intensive, and it is difficult to obtain fruitful
results from such research because the basis of experiments is very
different in each research field. In the social science field, for example,
several multi-agent simulation systems have been proposed for modeling
factors such as social interactions and language evolution, whereas
robotics researchers often use dynamics and sensor simulators. However,
there is no integrated system that uses both physical simulations and
social communication simulations.

Therefore, we have been developing a simulator environment called SIGVerse,
which is a simulator that combines dynamics, perception, and communication
simulations for synthetic approaches to research into the genesis of social
intelligence. In this paper, we introduce SIGVerse, its example application
and perspectives.

This keyword is innovated by Special Interest Group for SocioIntelliGenesis.
We focus on a synthetic research on elucidation of genesis of social intelligence -- physical interaction between body and environment, social interaction between agents and role of evolution and so on --, with aiming to understand intelligence of humans and robots. For such an approach, we have set interdisciplinal discussions with wide viewpoint for various research field such as cognitive science, developmental psycology, brain science, evolutionary biology and robotics.